Primary systemic (neoadjuvant) therapy is routinely used for locally advanced breast cancer patients before surgery to down-stage the disease and increase the chances of a successful outcome. Many patients though do not respond to neoadjuvant therapy, and may be better off switching to a different treatment regime, or progressing to surgery immediately. However, therapy monitoring is difficult because current clinical examination and x-ray/ultrasound mammography follow-ups correlate poorly with final therapy pathological outcome. Both magnetic resonance imaging (MRI) and positron emission tomography (PET) have been evaluated as early predictors of response, with studies showing that 18F-FDG PET as well as diffusion weighted (DW) MRI and choline-compounds MR spectroscopy (tCho-MRS) measurements correspond well with therapy success within a few weeks from the beginning of treatment. Unfortunately, availability (PET), complexity (tCho-MRS), and specificity (MRI) limit the applicability of these methods. Consequently, there is a need to develop non-invasive specific early prediction approaches that more easily integrate into medical practice. A potential answer may be offered by near infrared spectroscopy and tomography (NIRS-DOT). NIRS-DOT is a novel functional imaging technique that can offer images of tissue chromophores such as oxy (HbO) and deoxy hemoglobin (HbR), water and lipids, and small studies have hinted at its potential to predict therapy outcome with high accuracy as early as one week after the start of treatment. Further, recent technological advancements have permitted DOT to reach high time resolution (> 1Hz), allowing new types of functional information to be probed by dynamic imaging. In particular, our group has obtained promising initial results monitoring the response of breast tissue to external compression. Tissue viscoelastic response to compression causes hemodynamic (blood volume) changes with bi-phasic temporal profiles likely to differentiate healthy tissues from breast lesions. Further, the interplay of hemodynamics and tissue oxygen metabolism leads to hemoglobin oxygenation transients that offer the opportunity to estimate tissue oxygen consumption (OC) and blood flow (BF) from time-resolved optical data. The overall goal of this proposal is to combine MRI and NIRS-DOT to characterize the predictive value of compression-enabled measurements of tissue hemodynamics, blood flow and oxygen consumption as new biomarkers sensitive to therapy progress and quantify their relationship to final pathological outcome. Structural information from the MRI scans will be used as prior information for the optical reconstructions and dynamic optical and HbR-related MR blood oxygen level dependent (BOLD) images will be simultaneously acquired enabling a fusion approach for reconstructing time-resolved hemodynamic maps and BF/OC distributions. Difference BOLD images will be cross-validated against corresponding HbR maps. The work will culminate with a clinical trial to assess the early therapy outcome predictive ability of the new biomarkers.